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Fuzzy Logic - artificial intelligence:
In the above logic, we have been concerned with truth whether propositions and sentences are true. But, with some natural language statements, it is difficult to assign a "true" or "false" value. For instance, is the sentence: "Prince Charles is tall" true or false? Some people may say true, and others may say false, so there is an underlying probability that we might also want to represent. This can be attaining with so-called "fuzzy" logics. As such, the originator of fuzzy logics, Lotfi Zadeh, advocates not thinking about specific fuzzy logics but rather thinking about "fuzzification" of current theories, and this is starting to play a part in Artificial Intelligence. The arrangement of logics with programming agents and theories of probability to reason in the light of uncertain knowledge are important areas of Artificial Intelligence research. Various representation schemes such as Stochastic Logic Programs have an aspect of both logic and probability.
Classification of interrupts: 1. a) asynchronous external components or hardware malfunction 1.b)synchronous function of program state (for example over
Write short note on Quantization. Quantization: This is the first step in PCM. The whole amplitude range of the modulating signal is divided in a number of standard levels term
The C programming language is a standardized programming language forrned in the early 1970s by Ken Thompson and Dennis Ritchie for use on the UNIX operating system. It has since s
By using XNOR gate if the signals are similar then only the output will be one otherwise not.
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Subtract -27 from 68 using 2's complements. Ans. By using 2's complement 68-(-27)= 68-(-27) 2's complement representation of 68 = 01000100(64+4) 2's complement representatio
A component can handle its own events by executing the needed event-listener interface and adding itself as its own event listener.
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